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Ontology-Based Decision Support System for the Nitrogen Fertilization of Winter Wheat

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Metadata and Semantic Research (MTSR 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1355))

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Abstract

Digital technologies are already used in several aspects of agriculture. However, decision-making in crop production is still often a manual process that relies on various heterogeneous data sources. Small-scale farmers and their local consultants are particularly burdened by increasingly complex requirements. Regional circumstances and regulations play an essential role and need to be considered. This paper presents an ontology-based decision support system for the nitrogen fertilization of winter wheat in Bavaria, Germany. Semantic Web and Linked Data technologies were employed to both reuse and model new common semantic structures for interrelated knowledge. Many relevant general and regional data sources from multiple domains were not yet available in RDF. Hence, we used several tools to transform relevant data into corresponding OWL ontologies and combined them in a central knowledge base. The GUI application of the decision support system queries it to parameterize requests to external web services and to show relevant information in an integrated view. It further uses SPARQL queries to automatically generate recommendations for farmers and their consultants.

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Notes

  1. 1.

    https://www.eppo.int/RESOURCES/eppo_databases/eppo_codes.

  2. 2.

    https://www.ontotext.com/products/graphdb/.

  3. 3.

    https://www.qgis.org/en/site/.

References

  1. Albrecht, K., Martini, D., Schmitz, M.: Linked open data im Pflanzenschutz. In: GIL, pp. 19–24 (2019)

    Google Scholar 

  2. Aubin, S., Caracciolo, C., Zervas, P.: Landscaping the use of semantics to enhance the interoperability of agricultural data. Agrisemantics WG report (2017)

    Google Scholar 

  3. Bavarian State Ministry of Food, Agriculture and Forestry: Bavarian agricultural report. https://www.agrarbericht-2018.bayern.de. Accessed 16 Jul 2020

  4. Calvanese, D., et al.: Ontop: answering SPARQL queries over relational databases. Semant. Web 8(3), 471–487 (2017)

    Article  Google Scholar 

  5. Caracciolo, C., et al.: The AGROVOC linked dataset. Semant. Web 4(3), 341–348 (2013)

    Article  Google Scholar 

  6. Drury, B., Fernandes, R., Moura, M.F., de Andrade Lopes, A.: A survey of semantic web technology for agriculture. IPA 6(4), 487–501 (2019)

    Google Scholar 

  7. Hodgson, R., Mekonnen, D., Price, D., Hodges, J., Masters, J.E., Cox, S., Ray, S.: Quantities, units, dimensions and types (QUDT). http://www.qudt.org. Accessed 26 Feb 2020

  8. Jonquet, C., et al.: AgroPortal: a vocabulary and ontology repository for agronomy. COMPAG 144, 126–143 (2018)

    Google Scholar 

  9. Keil, J.M., Schindler, S.: Comparison and evaluation of ontologies for units of measurement. Semant. Web 10(1), 33–51 (2019)

    Article  Google Scholar 

  10. Laugwitz, B., Held, T., Schrepp, M.: Construction and evaluation of a user experience questionnaire. In: USAB, pp. 63–76 (2008)

    Google Scholar 

  11. Marienfeld, F., Schieferdecker, I., Lapi, E., Tcholtchev, N.: Metadata aggregation at GovData.de: an experience report. In: OpenSym, pp. 1–5 (2013)

    Google Scholar 

  12. Martini, D.: Webservices auf heterogenen Datenbeständen - Methoden der Umsetzung am Beispiel der KTBL-Planungsdaten. In: GIL, pp. 155–158 (2018)

    Google Scholar 

  13. Matteis, L., et al.: Crop ontology: vocabulary for crop-related concepts. In: S4BioDiv (2013)

    Google Scholar 

  14. Mawardi, S.Y., Abdel-Aziz, M.H., Omran, A.M., Mahmoud, T.A.: An ontology-driven decision support system for wheat production. IJCST 4(8), 11–17 (2013)

    Google Scholar 

  15. Nafissi, A., et al.: Wissensbasierte digitale Unterstützung in der Pflanzenbauberatung. In: GIL, pp. 145–150 (2019)

    Google Scholar 

  16. Perry, M., Herring, J.: GeoSPARQL - a geographic query language for RDF data. OGC Standard (2012)

    Google Scholar 

  17. Pokharel, S., Sherif, M.A., Lehmann, J.: Ontology based data access and integration for improving the effectiveness of farming in Nepal. In: WI-IAT, pp. 319–326 (2014)

    Google Scholar 

  18. Prud’hommeaux, E., Sequeda, J., Arenas, M., Bertails, A.: A direct mapping of relational data to RDF. W3C Recommendation (2012)

    Google Scholar 

  19. Publications Office of the European Union: EU vocabularies. https://op.europa.eu/en/web/eu-vocabularies. Accessed 3 Feb 2020

  20. Sklarß, S., Gattwinkel, D., Göldner, A., Horn, C., Wittig, C., Koroyin, O.: DCAT-AP.de Spezifikation: Deutsche Adaption des “Data Catalogue Application Profile” (DCAT-AP) für Datenportale in Europa. DCAT-AP.de Specification (2019)

    Google Scholar 

  21. Vatant, B., Wick, M., Kendall, E.: GeoNames ontology. https://www.geonames.org/ontology/documentation.html. Accessed 18 Feb 2020

  22. Vergara-Lozano, V., Medina-Moreira, J., Rochina, C., Garzón-Goya, M., Sinche-Guzmán, A., Bucaram-Leverone, M.: An ontology-based decision support system for the management of home gardens. In: CITI, pp. 47–59 (2017)

    Google Scholar 

  23. Vrandečić, D., Krötzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78–85 (2014)

    Article  Google Scholar 

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Acknowledgments

The research leading to these results has been funded by the Bavarian State Ministry of Food, Agriculture and Forestry (StMELF) under grant agreement no. D/17/02 in the project FarmExpert.

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Authors and Affiliations

  1. fortiss, Research Institute of the Free State of Bavaria associated with Technical University of Munich, Guerickestraße 25, 80805, Munich, Germany

    Ingmar Kessler, Alexander Perzylo & Markus Rickert

Authors
  1. Ingmar Kessler
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  2. Alexander Perzylo
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  3. Markus Rickert
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Corresponding author

Correspondence to Ingmar Kessler .

Editor information

Editors and Affiliations

  1. International Hellenic University, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Complutense University of Madrid, Madrid, Spain

    María-Antonia Ovalle-Perandones

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Kessler, I., Perzylo, A., Rickert, M. (2021). Ontology-Based Decision Support System for the Nitrogen Fertilization of Winter Wheat. In: Garoufallou, E., Ovalle-Perandones, MA. (eds) Metadata and Semantic Research. MTSR 2020. Communications in Computer and Information Science, vol 1355. Springer, Cham. https://doi.org/10.1007/978-3-030-71903-6_24

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  • DOI: https://doi.org/10.1007/978-3-030-71903-6_24

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  • Online ISBN: 978-3-030-71903-6

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